Evidence map›Paper›PMID 31973072›Full record

ArticleInsects2020

Expression Dynamics of Core RNAi Machinery Genes in Pea Aphids Upon Exposure to Artificially Synthesized dsRNA and miRNAs.

Li Yang, Yuan Tian, Yuan-Yuan Peng, Jinzhi Niu, Jin-Jun Wang

Open access · goldAbstract read
In one paragraph

Article in Insects, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Li YangKey Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing 400716, China.
Yuan TianKey Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing 400716, China.
Yuan-Yuan PengKey Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing 400716, China.
Jinzhi NiuKey Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing 400716, China.
Jin-Jun WangKey Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing 400716, China.
Southwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pea aphid is an important pest of vegetables and causes serious losses worldwide. RNA interference (RNAi) is an effective pest control tool, and three sub-pathways have been described: The miRNA pathway, siRNA pathway, and piRNA pathway. A large number of genes in miRNA pathway and piRNA pathway are found to be expanded. To study the roles of these genes, the expression of 25 core RNAi genes was screened in spatiotemporal samples, artificially synthesized dsRNA and miRNA treated samples. The 25 genes were all expressed during different development stages and in different tissues. In dsRNA-treated samples and miRNA-treated samples, the expressions of genes in these three pathways were induced, especially the expanded genes. This suggests a complex network of RNAi core genes in the three sub-pathways. Treatment of miRNA seems to induce gene expression in a dosage-dependent manner. These results increase our knowledge of the siRNA pathway and related factors from RNAi pathway in aphids and promote the use of RNAi for the control of aphid pests.

Indexed as

miRNA pathwaypea aphidspiRNA pathwaysiRNA pathway

Identifiers

PMID31973072
PMCPMC7074054
OpenAlexW3001882203

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.